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2001, 31, 303–331. [CrossRef]
79. Celada, F.; Seiden, P.E. A computer model of cellular interactions in the immune system. Immunol. Today
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80. Emerson, A.; Rossi, E. ImmunoGrid - the virtual human immune system project. Stud. Heal. Technol. Inf.
2007, 126, 87–92.
81. Halling-Brown, M.; Pappalardo, F.; Rapin, N.; Zhang, P.; Alemani, D.; Emerson, A.; Castiglione, F.; Duroux, P.;
Pennisi, M.; Miotto, O.; et al. ImmunoGrid: Towards agent-based simulations of the human immune system
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[CrossRef]
83. Warrender, C.; Forrest, S.; Koster, F. Modeling intercellular interactions in early Mycobacterium infection.
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84. Ghaffarizadeh, A.; Heiland, R.; Friedman, S.H.; Mumenthaler, S.M.; Macklin, P. PhysiCell: An open source
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85. Gilkes, D.M.; Semenza, G.L.; Wirtz, D. Hypoxia and the extracellular matrix: Drivers of tumour metastasis.
Nat. Rev. Cancer 2014, 14, 430–439. [CrossRef][PubMed]
86. Alfonso, J.C.L.; Talkenberger, K.; Seifert, M.; Klink, B.; Hawkins-Daarud, A.; Swanson, K.R.; Hatzikirou, H.;
Deutsch, A. The biology and mathematical modelling of glioma invasion: A review. J. R. Soc. Interface 2017,
14, 20170490. [CrossRef][PubMed]
87. Massey, S.C.; Rockne, R.C.; Hawkins-Daarud, A.; Gallaher, J.; Anderson, A.R.A.; Canoll, P.; Swanson, K.R.
Simulating PDGF-driven glioma growth and invasion in an anatomically accurate brain domain. Bull. Math. Biol.
2018, 80, 1292–1309. [CrossRef][PubMed]
88. Juliano, J.; Gil, O.; Hawkins-Daarud, A.; Noticewala, S.; Rockne, R.C.; Gallaher, J.; Massey, S.C.; Sims, P.A.;
Anderson, A.R.A.; Swanson, K.R.; et al. Comparative dynamics of microglial and glioma cell motility at the
infiltrative margin of brain tumours. J. R. Soc. Interface 2018, 15, 20170582. [CrossRef][PubMed]
89. Frascoli, F.; Flood, E.; Kim, P.S. A model of the effects of cancer cell motility and cellular adhesion properties
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90. Noonan, D.M.; De Lerma Barbaro, A.; Vannini, N.; Mortara, L.; Albini, A. Inflammation, inflammatory cells
and angiogenesis: Decisions and indecisions. Cancer Metastasis Rev. 2008, 27, 31–40. [CrossRef]
91. Tian, L.; Goldstein, A.; Wang, H.; Ching Lo, H.; Sun Kim, I.; Welte, T.; Sheng, K.; Dobrolecki, L.E.; Zhang, X.;
Putluri, N.; et al. Mutual regulation of tumour vessel normalization and immunostimulatory reprogramming.
Nature 2017, 544, 250–254. [CrossRef]
92. Uppal, A.; Wightman, S.C.; Ganai, S.; Weichselbaum, R.R.; An, G. Investigation of the essential role of
platelet-tumor cell interactions in metastasis progression using an agent-based model. Theor. Biol. Med. Model.
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93. Alfonso, J.C.L.; Schaadt, N.S.; Schönmeyer, R.; Brieu, N.; Forestier, G.; Wemmert, C.; Feuerhake, F.;
Hatzikirou, H. In-silico insights on the prognostic potential of immune cell infiltration patterns in the
breast lobular epithelium. Sci. Rep. 2016, 6, 33322. [CrossRef][PubMed]
94. Reddy, N.P.; Krouskop, T.A.; Newell, P.H. A computer model of the lymphatic system. Comput. Biol. Med.
1977, 7, 181–197. [CrossRef]
95. Jamalian, S.; Jafarnejad, M.; Zawieja, S.D.; Bertram, C.D.; Gashev, A.A.; Zawieja, D.C.; Davis, M.J.; Moore, J.E.
Demonstration and analysis of the suction effect for pumping lymph from tissue beds at subatmospheric
pressure. Sci. Rep. 2017, 7, 12080. [CrossRef][PubMed]
96. Jamalian, S.; Davis, M.J.; Zawieja, D.C.; Moore, J.E. Network scale modeling of lymph transport and its
effective pumping parameters. PLoS ONE 2016, 11, e0148384. [CrossRef][PubMed]
97. Jamalian, S.; Bertram, C.D.; Richardson, W.J.; Moore, J.E. Parameter sensitivity analysis of a lumped-parameter
model of a chain of lymphangions in series. Am. J. Physiol. Circ. Physiol. 2013, 305, H1709–H1717. [CrossRef]
[PubMed]
59
77. Baldazzi, V.; Castiglione, F.; Bernaschi, M. An enhanced agent based model of the immune system response.
Cell Immunol. 2006, 244, 77–79. [CrossRef][PubMed]
78. Bernaschi, M.; Castiglione, F. Design and implementation of an immune system simulator. Comput. Biol. Med.
2001, 31, 303–331. [CrossRef]
79. Celada, F.; Seiden, P.E. A computer model of cellular interactions in the immune system. Immunol. Today
1992, 13, 56–62. [CrossRef]
80. Emerson, A.; Rossi, E. ImmunoGrid - the virtual human immune system project. Stud. Heal. Technol. Inf.
2007, 126, 87–92.
81. Halling-Brown, M.; Pappalardo, F.; Rapin, N.; Zhang, P.; Alemani, D.; Emerson, A.; Castiglione, F.; Duroux, P.;
Pennisi, M.; Miotto, O.; et al. ImmunoGrid: Towards agent-based simulations of the human immune system
at a natural scale. Philos. Trans. R. Soc. A Math. Phys. Eng. Sci. 2010, 368, 2799. [CrossRef]
82. Perelson, A.S.; Ribeiro, R.M. Modeling the within-host dynamics of HIV infection. BMC Biol. 2013, 11, 96.
[CrossRef]
83. Warrender, C.; Forrest, S.; Koster, F. Modeling intercellular interactions in early Mycobacterium infection.
Bull. Math. Biol. 2006, 68, 2233–2261. [CrossRef][PubMed]
84. Ghaffarizadeh, A.; Heiland, R.; Friedman, S.H.; Mumenthaler, S.M.; Macklin, P. PhysiCell: An open source
physics-based cell simulator for 3-D multicellular systems. PLOS Comput. Biol. 2018, 14, e1005991. [CrossRef]
[PubMed]
85. Gilkes, D.M.; Semenza, G.L.; Wirtz, D. Hypoxia and the extracellular matrix: Drivers of tumour metastasis.
Nat. Rev. Cancer 2014, 14, 430–439. [CrossRef][PubMed]
86. Alfonso, J.C.L.; Talkenberger, K.; Seifert, M.; Klink, B.; Hawkins-Daarud, A.; Swanson, K.R.; Hatzikirou, H.;
Deutsch, A. The biology and mathematical modelling of glioma invasion: A review. J. R. Soc. Interface 2017,
14, 20170490. [CrossRef][PubMed]
87. Massey, S.C.; Rockne, R.C.; Hawkins-Daarud, A.; Gallaher, J.; Anderson, A.R.A.; Canoll, P.; Swanson, K.R.
Simulating PDGF-driven glioma growth and invasion in an anatomically accurate brain domain. Bull. Math. Biol.
2018, 80, 1292–1309. [CrossRef][PubMed]
88. Juliano, J.; Gil, O.; Hawkins-Daarud, A.; Noticewala, S.; Rockne, R.C.; Gallaher, J.; Massey, S.C.; Sims, P.A.;
Anderson, A.R.A.; Swanson, K.R.; et al. Comparative dynamics of microglial and glioma cell motility at the
infiltrative margin of brain tumours. J. R. Soc. Interface 2018, 15, 20170582. [CrossRef][PubMed]
89. Frascoli, F.; Flood, E.; Kim, P.S. A model of the effects of cancer cell motility and cellular adhesion properties
on tumour-immune dynamics. Math. Med. Biol. 2016, 34, dqw004. [CrossRef]
90. Noonan, D.M.; De Lerma Barbaro, A.; Vannini, N.; Mortara, L.; Albini, A. Inflammation, inflammatory cells
and angiogenesis: Decisions and indecisions. Cancer Metastasis Rev. 2008, 27, 31–40. [CrossRef]
91. Tian, L.; Goldstein, A.; Wang, H.; Ching Lo, H.; Sun Kim, I.; Welte, T.; Sheng, K.; Dobrolecki, L.E.; Zhang, X.;
Putluri, N.; et al. Mutual regulation of tumour vessel normalization and immunostimulatory reprogramming.
Nature 2017, 544, 250–254. [CrossRef]
92. Uppal, A.; Wightman, S.C.; Ganai, S.; Weichselbaum, R.R.; An, G. Investigation of the essential role of
platelet-tumor cell interactions in metastasis progression using an agent-based model. Theor. Biol. Med. Model.
2014, 11, 17. [CrossRef]
93. Alfonso, J.C.L.; Schaadt, N.S.; Schönmeyer, R.; Brieu, N.; Forestier, G.; Wemmert, C.; Feuerhake, F.;
Hatzikirou, H. In-silico insights on the prognostic potential of immune cell infiltration patterns in the
breast lobular epithelium. Sci. Rep. 2016, 6, 33322. [CrossRef][PubMed]
94. Reddy, N.P.; Krouskop, T.A.; Newell, P.H. A computer model of the lymphatic system. Comput. Biol. Med.
1977, 7, 181–197. [CrossRef]
95. Jamalian, S.; Jafarnejad, M.; Zawieja, S.D.; Bertram, C.D.; Gashev, A.A.; Zawieja, D.C.; Davis, M.J.; Moore, J.E.
Demonstration and analysis of the suction effect for pumping lymph from tissue beds at subatmospheric
pressure. Sci. Rep. 2017, 7, 12080. [CrossRef][PubMed]
96. Jamalian, S.; Davis, M.J.; Zawieja, D.C.; Moore, J.E. Network scale modeling of lymph transport and its
effective pumping parameters. PLoS ONE 2016, 11, e0148384. [CrossRef][PubMed]
97. Jamalian, S.; Bertram, C.D.; Richardson, W.J.; Moore, J.E. Parameter sensitivity analysis of a lumped-parameter
model of a chain of lymphangions in series. Am. J. Physiol. Circ. Physiol. 2013, 305, H1709–H1717. [CrossRef]
[PubMed]
59